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Researchers Use Mass Spec, Microdissection to ID 11-Protein Prognostic Signature in Breast Cancer


Researchers at Rotterdam's Erasmus University Medical Center have identified an 11-protein signature that appears to distinguish between more and less aggressive forms of triple-negative breast cancer.

Based on their findings, which were detailed in a study published this month in the Journal of the National Cancer Institute, more than 60 percent of triple-negative breast cancer patients given adjuvant chemotherapy based upon current standards of care could avoid such treatment, Arzu Umar, an Erasmus researcher and author on the paper, told ProteoMonitor.

She and her colleagues now aim to develop multiple-reaction monitoring mass spec assays to the 11 proteins, which they hope to use in prospective validation studies looking at an expanded number of patients.

Triple-negative breast cancer – cancer in which the tumor does not express estrogen receptor, progesterone receptor, or Her2 – is one of the most aggressive forms of the disease and one for which there are currently no targeted therapies.

As the JNCI authors noted, roughly 30 percent of lymph-node negative triple-negative patients develop distant metastasis. And while this set of patients could potentially benefit from adjuvant chemotherapy, this, they observed, leaves roughly 70 percent of patients receiving unnecessary treatment.

"Roughly 70 percent of triple-negative breast cancer patients are cured by surgery alone," Umar said. "So if you could predict that somebody wouldn't need adjuvant chemotherapy, then maybe physicians would be more careful giving it."

The researchers performed their analysis in frozen primary tumors collected from 126 lymph node-negative and adjuvant therapy-naive patients, running them in two sets – a 63-sample training set, in which they identified the 11-protein signature, and a multi-center 63-sample test set, which they used to validate this signature.

The signature was able to distinguish between patients with poor prognosis – who would likely benefit from adjuvant therapy – from those with good prognosis – who would not benefit – with 89.5 percent sensitivity and 70.5 percent specificity. Good prognosis was defined as patients who remained free of distant metastases for at least five years after surgery.

Compared to the typical discovery proteomics effort, the JNCI study employed a large number of clinical samples — a key factor, Umar said, in the researchers' ability to identify a relatively well performing signature.

"There is a lot of proteomics going on with clinical samples," she noted, "but usually people have [for instance] 10 patients in one group and 10 patients in the other."

Collecting clinical material for the project was a significant undertaking, she added, particularly given that current standard of care calls for all triple-negative patients to receive adjuvant chemo. Because of this, the study used archival material from the 1980s when standard of care in the Netherlands did not call for adjuvant treatment.

In addition to the large number of samples used, the project was somewhat unique in that the researchers laser capture microdissected all of their samples.

LCM uses a laser coupled to a microscope to allow pathologists to isolate particular portions of a sample of interest with high precision. The procedure potentially improves proteomic analyses by allowing researchers to remove stromal cells that could mask the protein content of tumor cells.

The technique, however, typically results in sample sizes too small to perform biomarker discovery on mass spec, and so is more commonly used to prepare samples for antibody-based analyses like reverse phase protein arrays.

Mass spec-based profiling of LCM tumors is possible, however, Umar said, citing the use of modified dedicated LC columns and extra long gradients as key.

"What we have been doing is using dedicated columns that are longer than standard columns and with a narrowed inner diameter," she said. "And if you then run a longer gradient – a three-hour LC gradient – you can get the kind of depth you need in order to do proper biomarker discovery on [LCM] samples."

LCM "gives you a very homogeneous sample set," Umar noted. "Breast cancer tissue is very heterogeneous, and if you just make a crude lysate you can have proteins from all different kinds of cells."

In addition to providing a more homogenous sample set, LCM removes high abundance proteins present in stromal cells, helping mass spec penetrate into lower abundance tumor proteins.

"If you make a whole lysate, then you have so much stromal protein that in our experience your total number of protein identifications goes down severely because the stroma consists of collagens and very high abundance supportive proteins – it's like analyzing serum," Umar said.

Using a Thermo Scientific LTQ Orbitrap XL for their analysis, the researchers were able to identify in the range of 1,000 to 1,500 proteins in their microdissected samples. Umar said that she and her colleagues are now performing similar analyses on the newer Thermo Scientific Q Exactive machine and hope in the next six months or so to try out their workflow on the recently released Fusion Orbitrap.

With these newer instruments the researchers hope to collect quantitative data on around 5,000 proteins in LCM samples, she said, noting that her lab uses LCM for basically all of their biomarker discovery work in tissue.

The method is not without its difficulties, though, Umar said. In addition to limiting the amount of sample available for analysis, it can also be quite time consuming. LCM of the two 63-sample sets analyzed in the JNCI study required around six months per set.

The researchers are now working on MRM assays to the 11 proteins in their signature, Umar said, adding that eventually she and her colleagues aim to use the assays in prospective clinical trials in order to do a larger scale validation of their signature.

Ultimately, they hope to demonstrate that "maybe [current] standard of care isn't always necessary if you take into account that it costs a lot of money and places a heavy burden on the patient," she said. "To get there, though, we need to do prospective clinical trials to prove that this is actually the case."